Digital images having depicted therein an object inclusive of documents such as a letter, a check, a bill, an invoice, etc. have conventionally been captured and processed using a scanner or multifunction peripheral (MFP) coupled to a computer workstation such as a laptop or desktop computer. Methods and systems capable of performing such capture and processing are well known in the art and well adapted to the tasks for which they are employed.
More recently, the conventional scanner-based and MFP-based image capture and processing applications have shifted toward mobile platforms, e.g. as described in the related patent applications noted above with respect to capturing and processing images using mobile devices (U.S. Pat. No. 8,855,375), classifying objects depicted in images captured using mobile devices (U.S. Pat. No. 9,355,312, e.g. at column 9, line 9—column 15, line 28), and extracting data from images captured using mobile devices (U.S. Patent Publication No. 9,311,531, e.g. at column 18, line 25—column 27, line 16).
While these capture, processing, classification and extraction engines and methods are capable of reliably extracting information from certain objects or images, it is not possible to dynamically extract information from other objects, particularly objects characterized by a relatively complex background, and/or overlapping regions of foreground (e.g. text) and background. In practice, while it may be possible to reliably extract information from a simple document having a plain white background with dark foreground text and/or images imposed thereon, a document depicting one or more graphics (such as pictures, logos, etc.) as the background with foreground text and/or images imposed thereon, especially if overlapping.
This problem arises primarily because it becomes significantly difficult to distinguish the foreground from the background, especially in view of the fact that digital images are conventionally converted to bitonal (black/white) or grayscale color depth prior to attempting extraction. As a result, tonal differences between background and foreground are suppressed in converting the color channel information into grayscale intensity information or bitonal information.
This is an undesirable limitation that restricts users from using powerful extraction technology on an increasingly diverse array of documents encountered in the modern world and which are useful or necessary to complete various mobile device-mediated transactions or business processes.
For example, it is common for financial documents such as checks, credit cards, etc. to include graphics, photographs, or other imagery and/or color schemes as background upon which important financial information are displayed. The font and color of the foreground financial information may also vary from “standard” business fonts and/or colors, creating additional likelihood that discriminating between the foreground and background will be difficult or impossible.
Similarly, identifying documents such as driver's licenses, passports, employee identification, etc. frequently depict watermarks, holograms, logos, seals, pictures, etc. over which important identifying information may be superimposed in the foreground. To the extent these background and foreground elements overlap, difficulties are introduced into the discrimination process, frustrating or defeating the ability to extract those important information.
Therefore, it would be highly beneficial to provide new method, system and/or computer program product technology for extracting information from complex digital image data depicting highly similar foreground and background elements, and/or overlapping background and foreground elements.